The standard cortical model assumes that the meaning of a neuron's signal is contained in its firing rate. While that model has been used to interpret a voluminous amount of experimental data, it does not address ...
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The standard cortical model assumes that the meaning of a neuron's signal is contained in its firing rate. While that model has been used to interpret a voluminous amount of experimental data, it does not address the question of timing, or how recipient neurons can decode this signal in time to predict behavioral results. We propose a model based on coincident firing of large groups of neurons. We show using an example of predictive coding, how the cortex can support vast amounts of non-interfering parallel computation. (C) 2000 Published by Elsevier Science B.V. All rights reserved.
In this work we tackle the problem of error propagation that packet losses can cause in commonly used predictive video coding environments. Using unbalanced multiple description coding (UMDC) to generate redundant sou...
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In this work we tackle the problem of error propagation that packet losses can cause in commonly used predictive video coding environments. Using unbalanced multiple description coding (UMDC) to generate redundant source data, we apply the consistency sequence estimation (CSE) algorithm for estimating the lost data. The CSE algorithm, proposed by Singh and Ortega for a 1-D input source signal in a DPCM context, uses a sequence search to verify the consistency of the estimates with the received data. The novelty of our work is the extension of the CSE algorithm to a block matching ME/MC video coder (such as H.263). To reach this aim we propose to work in the spatial domain. Among the advantages of the proposed error resilience scheme are its low-complexity and its compatibility with standard video coders.
Unconstrained motion compensated temporal filtering (UMCTF) is a very general and flexible framework for temporal filtering. It allows the selection of many different filters as well as decomposition structures to all...
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Unconstrained motion compensated temporal filtering (UMCTF) is a very general and flexible framework for temporal filtering. It allows the selection of many different filters as well as decomposition structures to allow easy adaptation to video content, bandwidth variations, complexity requirements, and in conjunction with embedded coding can provide spatio-temporal-SNR scalability. In this paper we demonstrate the content-adaptive filter selection provided within the UMCTF framework. We show improvements in coding efficiency as well as in decoded visual quality using content-adaptive filters, at different granularities.
A lot of techniques have been developed for the encoding of triangular meshes as this is a widely used representation for the description of surface models. Although methods for the encoding of the neighbor informatio...
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A lot of techniques have been developed for the encoding of triangular meshes as this is a widely used representation for the description of surface models. Although methods for the encoding of the neighbor information, the connectivity, are near optimal, there is still room for better en-codings of vertex locations, the geometry. Our geometry encoding strategy follows the predictive coding paradigm, which is based on a region growing encoding order. Only the delta vectors between original and predicted locations are encoded in a local coordinate system, which splits into two tangential and one normal component. In this paper we introduce so-called higher order prediction for an improved encoding of the normal component. We first encode the tangential components with parallelogram prediction. Then we fit a higher order surface to the so far encoded geometry. As we encode the normal component as a bending angle, it is found by intersecting the higher order surface with the circle defined by the tangential components. Experimental results show that our strategy allows saving one bit per vertex for the normal component independent of the tangential prediction rule used.
We propose an algorithm intended for compression of medical images, which allows for embedded coding in L/sub /spl infin// sense, i.e., progressive near-lossless as well as lossless image compression. The method is ba...
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We propose an algorithm intended for compression of medical images, which allows for embedded coding in L/sub /spl infin// sense, i.e., progressive near-lossless as well as lossless image compression. The method is based on a lossy plus near-lossless layered compression scheme and embedded quantization of the difference signal. We show, that this technique allows for a better image quality and compression performance for large tolerance values than algorithms based on predictive coding. The lossy plus near-lossless scheme also allows for image reconstruction with a minimum mean square error (MSE) criterion, while providing a strict control of the maximum absolute difference error. This property is impossible in predictive coding algorithms.
We propose a novel approach for light field compression that incorporates disparity compensation into 4D wavelet coding using disparity-compensated lifting. With this approach, we obtain the benefits of wavelet coding...
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We propose a novel approach for light field compression that incorporates disparity compensation into 4D wavelet coding using disparity-compensated lifting. With this approach, we obtain the benefits of wavelet coding, including compression efficiency and scalability in all dimensions. Additionally, our proposed approach solves the irreversibility limitations of previous wavelet coding approaches. Experimental results show that the compression efficiency of the proposed technique outperforms current state-of-the-art wavelet coding techniques by a wide margin.
This paper presents an information-theoretic study of video codecs that are based on the principle of source coding with side information at the decoder. In contrast to the classical Wyner-Ziv side-information source ...
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This paper presents an information-theoretic study of video codecs that are based on the principle of source coding with side information at the decoder. In contrast to the classical Wyner-Ziv side-information source coding problem (1976), in this work we address the situation where the source and side-information are connected through a state of nature that is unknown to both the encoder and the decoder. We dub this framework as source encoding with side-information under ambiguous state of nature (SEASON). Our objective is to compare the achievable rate-distortion (R/D) performance of conventional video codecs designed under the motion-compensated predictive coding (MCPC) framework and video codecs designed under the SEASON framework. Our analysis shows that under appropriate motion models and for Gaussian displaced frame difference (DFD) statistics, the R/D performance of a classical MCPC-based video codec is matched by that of our proposed SEASON-based video codec, with the hitter being characterized by the novel concept of moving the motion compensation task from the encoder to the decoder.
This paper presents a memory-saving long-term prediction algorithm. It takes advantage of the better image quality possible with this technique, but is characterized by an extreme reduction in the amount of memory spa...
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This paper presents a memory-saving long-term prediction algorithm. It takes advantage of the better image quality possible with this technique, but is characterized by an extreme reduction in the amount of memory space required. In reference picture selection mode (H.263 standard, Annex N), coder and decoder use not only the previous picture for prediction, but also information from less recent pictures. Contrary to Annex N, in the method that we propose only parts, e.g. individual blocks or areas of past pictures, are stored in a reference buffer. We present two new concepts, both for selecting picture areas for storing and for deleting superfluous blocks from the long-term memory. By suitable selection of the picture areas, our algorithm achieves a similar picture quality to H.263+, Annex N, but uses only a fraction of the picture buffer. In this way it is possible to address around 50 earlier pictures with the same amount of memory required for only 5 pictures. Moreover, our approach requires no signaling and produces no delay.
Compressed bit streams of 3D mesh data are highly vulnerable to transmission errors due to predictive coding and entropy coding. In this work, we propose an error resilient and progressive coding scheme for 3D meshes....
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ISBN:
(纸本)0780377508
Compressed bit streams of 3D mesh data are highly vulnerable to transmission errors due to predictive coding and entropy coding. In this work, we propose an error resilient and progressive coding scheme for 3D meshes. To make a compressed bit stream robust to transmission errors, 3D mesh data is partitioned into several segments, which are then encoded independently. In the decoder, a novel error concealment scheme is employed to improve the visual quality of corrupted segments. Simulation results show that the proposed algorithm provides a good quality reconstruction even in severe error conditions.
Highly scalable video compression based on invertible motion adaptive lifting transforms has emerged as a promising area in image processing research and an important component in interactive multimedia technology. Ho...
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Highly scalable video compression based on invertible motion adaptive lifting transforms has emerged as a promising area in image processing research and an important component in interactive multimedia technology. However, within this feed-forward framework, the potential for coding efficiency improvement and its impact on random accessibility still has not been carefully assessed. In this paper, we compare the merits of several three-dimensional context coding strategies from an information-theoretic perspective. The variation in random access cost in response to coding parameter adjustments is analyzed, for a variety of spatial and temporal configurations.
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